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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BioMedical_NER-maccrobat-distilbert
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# BioMedical_NER-maccrobat-distilbert
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3622
- Precision: 0.8525
- Recall: 0.9225
- F1: 0.8861
- Accuracy: 0.9419
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 45 | 1.7742 | 0.6341 | 0.0055 | 0.0109 | 0.6272 |
| No log | 2.0 | 90 | 1.4622 | 0.3671 | 0.1659 | 0.2286 | 0.6546 |
| No log | 3.0 | 135 | 1.2643 | 0.3409 | 0.2941 | 0.3158 | 0.6742 |
| No log | 4.0 | 180 | 1.1501 | 0.4039 | 0.4283 | 0.4157 | 0.7028 |
| No log | 5.0 | 225 | 1.0938 | 0.4145 | 0.5229 | 0.4624 | 0.7098 |
| No log | 6.0 | 270 | 1.0439 | 0.4371 | 0.5780 | 0.4978 | 0.7257 |
| No log | 7.0 | 315 | 0.9442 | 0.4997 | 0.6147 | 0.5513 | 0.7583 |
| No log | 8.0 | 360 | 0.9376 | 0.5126 | 0.6591 | 0.5767 | 0.7629 |
| No log | 9.0 | 405 | 0.8024 | 0.5512 | 0.6753 | 0.6070 | 0.7921 |
| No log | 10.0 | 450 | 0.7367 | 0.5949 | 0.6842 | 0.6364 | 0.8121 |
| No log | 11.0 | 495 | 0.7276 | 0.5959 | 0.7209 | 0.6525 | 0.8222 |
| 1.0374 | 12.0 | 540 | 0.6606 | 0.6329 | 0.7289 | 0.6775 | 0.8369 |
| 1.0374 | 13.0 | 585 | 0.6466 | 0.6335 | 0.7530 | 0.6881 | 0.8423 |
| 1.0374 | 14.0 | 630 | 0.6825 | 0.6200 | 0.7716 | 0.6875 | 0.8397 |
| 1.0374 | 15.0 | 675 | 0.5721 | 0.6767 | 0.7777 | 0.7237 | 0.8657 |
| 1.0374 | 16.0 | 720 | 0.5446 | 0.6965 | 0.7876 | 0.7393 | 0.8771 |
| 1.0374 | 17.0 | 765 | 0.5136 | 0.7475 | 0.7881 | 0.7672 | 0.8872 |
| 1.0374 | 18.0 | 810 | 0.5248 | 0.7185 | 0.8218 | 0.7667 | 0.8866 |
| 1.0374 | 19.0 | 855 | 0.4944 | 0.7494 | 0.8284 | 0.7869 | 0.8961 |
| 1.0374 | 20.0 | 900 | 0.5092 | 0.7299 | 0.8391 | 0.7807 | 0.8920 |
| 1.0374 | 21.0 | 945 | 0.4491 | 0.7775 | 0.8393 | 0.8072 | 0.9083 |
| 1.0374 | 22.0 | 990 | 0.4400 | 0.7744 | 0.8537 | 0.8121 | 0.9104 |
| 0.3072 | 23.0 | 1035 | 0.4593 | 0.7689 | 0.8619 | 0.8128 | 0.9091 |
| 0.3072 | 24.0 | 1080 | 0.4547 | 0.7726 | 0.8670 | 0.8171 | 0.9094 |
| 0.3072 | 25.0 | 1125 | 0.4425 | 0.7825 | 0.8689 | 0.8234 | 0.9141 |
| 0.3072 | 26.0 | 1170 | 0.4229 | 0.7949 | 0.8712 | 0.8313 | 0.9184 |
| 0.3072 | 27.0 | 1215 | 0.4015 | 0.8192 | 0.8731 | 0.8453 | 0.9241 |
| 0.3072 | 28.0 | 1260 | 0.4222 | 0.7995 | 0.8771 | 0.8365 | 0.9197 |
| 0.3072 | 29.0 | 1305 | 0.4119 | 0.8017 | 0.8849 | 0.8413 | 0.9217 |
| 0.3072 | 30.0 | 1350 | 0.3960 | 0.8217 | 0.8864 | 0.8528 | 0.9276 |
| 0.3072 | 31.0 | 1395 | 0.3965 | 0.8204 | 0.8919 | 0.8547 | 0.9278 |
| 0.3072 | 32.0 | 1440 | 0.3936 | 0.8222 | 0.8972 | 0.8581 | 0.9282 |
| 0.3072 | 33.0 | 1485 | 0.3979 | 0.8263 | 0.8991 | 0.8612 | 0.9299 |
| 0.1369 | 34.0 | 1530 | 0.3799 | 0.8352 | 0.8989 | 0.8659 | 0.9333 |
| 0.1369 | 35.0 | 1575 | 0.3712 | 0.8407 | 0.9054 | 0.8718 | 0.9356 |
| 0.1369 | 36.0 | 1620 | 0.3648 | 0.8443 | 0.9046 | 0.8734 | 0.9368 |
| 0.1369 | 37.0 | 1665 | 0.3640 | 0.8414 | 0.9048 | 0.8719 | 0.9368 |
| 0.1369 | 38.0 | 1710 | 0.3632 | 0.8473 | 0.9088 | 0.8770 | 0.9385 |
| 0.1369 | 39.0 | 1755 | 0.3765 | 0.8369 | 0.9118 | 0.8727 | 0.9363 |
| 0.1369 | 40.0 | 1800 | 0.3686 | 0.8465 | 0.9107 | 0.8775 | 0.9382 |
| 0.1369 | 41.0 | 1845 | 0.3644 | 0.8461 | 0.9158 | 0.8796 | 0.9389 |
| 0.1369 | 42.0 | 1890 | 0.3676 | 0.8446 | 0.9156 | 0.8786 | 0.9390 |
| 0.1369 | 43.0 | 1935 | 0.3667 | 0.8451 | 0.9177 | 0.8799 | 0.9397 |
| 0.1369 | 44.0 | 1980 | 0.3622 | 0.8502 | 0.9189 | 0.8832 | 0.9407 |
| 0.0844 | 45.0 | 2025 | 0.3628 | 0.8535 | 0.9187 | 0.8849 | 0.9410 |
| 0.0844 | 46.0 | 2070 | 0.3677 | 0.8510 | 0.9198 | 0.8840 | 0.9406 |
| 0.0844 | 47.0 | 2115 | 0.3670 | 0.8521 | 0.9229 | 0.8861 | 0.9410 |
| 0.0844 | 48.0 | 2160 | 0.3627 | 0.8532 | 0.9227 | 0.8866 | 0.9417 |
| 0.0844 | 49.0 | 2205 | 0.3640 | 0.8511 | 0.9232 | 0.8857 | 0.9417 |
| 0.0844 | 50.0 | 2250 | 0.3622 | 0.8525 | 0.9225 | 0.8861 | 0.9419 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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